7/2/2023 0 Comments M1 mac handbrake![]() ![]() While Macs might not be known for gaming, that perception is changing. Notably, it also beats the M1 Pro in Photoshop, which scores an 806, though it falls slightly behind the M1 Max which scores an 887 in the same Photoshop benchmark. This means the Apple M1 Ultra is about 65% faster than the M2, but again, this is an expected result given that the M1 Ultra is a desktop-class processor, while the M2 is a hybrid desktop/mobile processor.Ĭompared to the M1, which scores a 354 on PugetBench’s Adobe Premiere Pro benchmark, The M2 comes out about 56% better than the M1, and on the Photoshop benchmark, it comes out about 26% higher than the M1. The Apple M2 meanwhile, scored 817 and 552, respectively, on the same tests. It scored 1,010 in PugetBench for Adobe Photoshop and 1,354 for PugetBench for Adobe Premiere Pro. When it comes to PugetBench for Adobe Photoshop and PugetBench for Adobe Premiere Pro, it’s a similar result with the M1 Ultra coming out way ahead of the pack, which is expected. ![]() This is also about 57% of the speed of the M1 Ultra, which is not bad at all for a mobile workstation. In terms of Apple-to-Apple comparisons, this is about 15% faster than its M1 predecessor, which is a solid gen-on-gen improvement. The M2 chip did an admirable job, encoding the same video at 54 fps, while the M1 chip encoded it at 47 fps. In Handbrake, the M1 Ultra encoded Tears of Steel at into at about 94 frames per second (fps), while the next closest, the M1 Max and M1 Pro, were able to encode that same video at 76 fps. In terms of creative benchmarks, it’s no surprise that the M1 Ultra packed into the Mac Studio is the absolute winner here. Creative workloads are what make MacBooks some of the best laptops around, so how the M-series chips handle various tasks is an important matter. If your Jellyfin server does not support hardware acceleration, but you have another machine that does, you can leverage rffmpeg to delegate the transcoding to another machine.Well, what about creative performance? This is the Apple M-series bread and butter, after all, so this is what a lot of people are going to want to look at. The hardware acceleration is available immediately for media playback. ![]() Supported codecs need to be indicated by checking the boxes in Enable hardware decoding for and Hardware encoding options. Select a valid hardware acceleration method from the drop-down menu and a device if applicable. Hardware acceleration options can be found in the Admin Dashboard under the Transcoding section of the Playback tab. The current state of hardware acceleration support in FFmpeg can be checked on the rpi-ffmpeg repository. Jellyfin will fallback to software de/encoding for those usecases. This decision was made because Raspberry Pi is currently migrating to a V4L2 based hardware acceleration, which is already available in Jellyfin but does not support all features other hardware acceleration methods provide due to lacking support in FFmpeg. Video Scaling & Format conversion (optional)Īs of Jellyfin 10.8 hardware acceleration on Raspberry Pi via OpenMAX OMX was dropped and is no longer available. The transcoding pipeline usually has multiple stages, which can be simplified to: Raspberry Pi Video4Linux2 (V4L2, Linux only) Intel/AMD Video Acceleration API (VA-API, Linux only) The supported and validated video hardware acceleration (HWA) methods are: It enables the Jellyfin server to access the fixed-function video codecs, video processors and GPGPU computing interfaces provided by vendor of the installed GPU and the operating system. The Jellyfin server uses a modified version of FFmpeg as its transcoder, namely jellyfin-ffmpeg. The Jellyfin server can offload on the fly video transcoding by utilizing an integrated or discrete graphics card ( GPU) suitable to accelerate this workloads very efficiently without straining your CPU. ![]()
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